High dimensional model representation of log likelihood ratio: binary classification with SNP data

BACKGROUND: Developing binary classification rules based on SNP observations has been a major challenge for many modern bioinformatics applications, e.g., predicting risk of future disease events in complex conditions such as cancer. Small-sample, high-dimensional nature of SNP data, weak effect of...

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Detalles Bibliográficos
Autores principales: pour, Ali Foroughi, Pietrzak, Maciej, Sucheston-Campbell, Lara E., Karaesmen, Ezgi, Dalton, Lori A., Rempała, Grzegorz A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7504683/
https://www.ncbi.nlm.nih.gov/pubmed/32957998
http://dx.doi.org/10.1186/s12920-020-00774-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7504683/
https://www.ncbi.nlm.nih.gov/pubmed/32957998
http://dx.doi.org/10.1186/s12920-020-00774-1

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